Canary:an Interactive and Query-Based Approach to Extract Requirements from Online Forums

Abstract

Interactions among stakeholders and engineers is key to Requirements engineering (RE). Increasingly, such interactions take place online, producing large quantities of qualitative (natural language) and quantitative (e.g., votes) data. Although a rich source of requirements-related information, extracting such information from online forums can be nontrivial.We propose Canary, a tool-assisted approach, to facilitate systematic extraction of requirements-related information from online forums via high-level queries. Canary (1) adds structure to natural language content on online forums using an annotation schema combining requirements and argumentation ontologies, (2) stores the structured data in a relational database, and (3) compiles high-level queries in Canary syntax to SQL queries that can be run on the relational database.We demonstrate key steps in Canary workflow, including (1) extracting raw data from online forums, (2) applying annotations to the raw data, and (3) compiling and running interesting Canary queries that leverage the social aspect of the data.

Publication DOI: https://doi.org/10.1109/RE.2017.84
Divisions: College of Engineering & Physical Sciences
Additional Information: © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Event Title: 25th IEEE International Requirements Engineering Conference, RE 2017
Event Type: Other
Event Dates: 2017-09-04 - 2017-09-08
Uncontrolled Keywords: Software,Safety, Risk, Reliability and Quality,Management of Technology and Innovation
ISBN: 9781538631911
Last Modified: 04 Mar 2024 08:08
Date Deposited: 04 Jan 2018 12:25
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Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Conference contribution
Published Date: 2017-09-26
Published Online Date: 2017-09-26
Accepted Date: 2017-09-26
Authors: Kanchev, Georgi M.
Murukannaiah, Pradeep K.
Chopra, Amit K.
Sawyer, Peter (ORCID Profile 0000-0001-8044-2738)

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